| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """Lyrics dataset parsed from Genius""" | |
| import csv | |
| import json | |
| import os | |
| import gzip | |
| import datasets | |
| _CITATION = """\ | |
| @InProceedings{huggingartists:dataset, | |
| title = {Lyrics dataset}, | |
| author={Aleksey Korshuk | |
| }, | |
| year={2021} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| This dataset is designed to generate lyrics with HuggingArtists. | |
| """ | |
| # Add a link to an official homepage for the dataset here | |
| _HOMEPAGE = "https://github.com/AlekseyKorshuk/huggingartists" | |
| # Add the licence for the dataset here if you can find it | |
| _LICENSE = "All rights belong to copyright holders" | |
| _URL = "https://huggingface.co/datasets/huggingartists/enya/resolve/main/datasets.json" | |
| # Name of the dataset | |
| class LyricsDataset(datasets.GeneratorBasedBuilder): | |
| """Lyrics dataset""" | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| # This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
| features = datasets.Features( | |
| { | |
| "text": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, # Here we define them above because they are different between the two configurations | |
| # If there's a common (input, target) tuple from the features, | |
| # specify them here. They'll be used if as_supervised=True in | |
| # builder.as_dataset. | |
| supervised_keys=None, | |
| # Homepage of the dataset for documentation | |
| homepage=_HOMEPAGE, | |
| # License for the dataset if available | |
| license=_LICENSE, | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| # This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
| # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
| # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs | |
| # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
| # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
| data_dir = dl_manager.download_and_extract(_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": data_dir, | |
| "split": "train", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, split): | |
| """Yields examples as (key, example) tuples.""" | |
| # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
| with open(filepath, encoding="utf-8") as f: | |
| data = json.load(f) | |
| for id, pred in enumerate(data[split]): | |
| yield id, {"text": pred} |